ChatGPT vs OpenAI API - Key Differences and Use Cases

ChatGPT is the hosted chat application from OpenAI. Whereas a custom chatbot built using the OpenAI API, although uses similar underlying language models (e.g., GPT-3.5, GPT-4, etc.), there are several important differences in capabilities, customization, pricing, integration, and control.

Are you interested in a ChatGPT like experience on your website? Check out this guide to get started.

ChatGPT vs OpenAI API

Let us look at each item one by one.

1. Hosting and Access

ChatGPT

• No installation required: Since ChatGPT is provided as a web interface, there is no deployment or server setup needed on your part.
• Limited UI customization: The interface is standardized, with only minor adjustments possible (e.g., switching themes). The core user experience is the same for everyone.
• Hosted by OpenAI: ChatGPT (accessible at https://chat.openai.com/) is fully hosted by OpenAI. End-users simply log in to the website to interact with it.

Chatbot via OpenAI API

• Full UI control: You control the front-end experience—how users interact, the look and feel of the chatbot widget. You can read more about the customizations possible in the predictable dialogs integration here.
• Flexibility in access points: You can embed the chatbot in websites, mobile apps, or any platform you wish.
• Hosting: You can write the code, deploy it to your servers or cloud platforms, and handle infrastructure considerations like uptime, load balancing, etc. Alternatively, You can use a service like we offer where you don't have to worry about hosting - You can read more about that in this post -

2. Customization and Prompt Engineering

ChatGPT

• General-purpose tuning: ChatGPT is optimized to be a highly capable, general-purpose chatbot. You can provide prompts and context in the conversation, but there are limits to how you can customize its “system” behavior and memory across long sessions.
• Limited system-level customization: While ChatGPT does accept some hidden system prompts for better control, as an end-user you can’t fully override or modify the underlying instructions that guide ChatGPT’s overall style and policies.

Chatbot via OpenAI API

• Prompt engineering control: You have full control over system, user, and assistant messages in the API call. You can craft a detailed “system prompt” that guides the overall behavior of the model (e.g., a specific brand voice, domain constraints, or role-play scenarios).
• Custom logic: You can insert logic in your code that decides how to prompt the model, handle the responses, chain multiple calls to refine the answer, etc.
• Custom fine-tuning (for older GPT-3 family models): You can further tailor some GPT models to your domain-specific data through the fine-tuning API (note that GPT-4 fine-tuning is not generally available at the time of this writing, but may be in the future).

Reason: The API is built for developers who need full control over the prompt and conversation flows. ChatGPT, on the other hand, is a pre-built solution focused on a broad range of tasks.

3. Data Control and Privacy

ChatGPT

• User-level data: ChatGPT saves conversation history for a certain period (unless you manually delete it or disable history in your account settings). OpenAI may use these interactions for model improvements, adhering to their Data Usage Policy (subject to change).
• Less direct control: Since ChatGPT is a hosted solution, you rely on OpenAI’s data handling and privacy measures without the ability to fine-tune the data policies on a per-use-case basis.

Chatbot via OpenAI API

• Possibility to store data privately: You can decide how and where to store user interactions in your own databases. This can be critical for compliance with specific data regulations or internal privacy rules.
• Customization of data handling: You can choose what user information to log, how long to keep it, and how to anonymize it. You also have more options to comply with specific privacy regulations (e.g., GDPR).

Reason: Using the OpenAI API shifts responsibility for data management from OpenAI to you, allowing for more granular control but also requiring you to maintain security and compliance.

4. Pricing and Usage Costs

ChatGPT

• ChatGPT (free tier): ChatGPT has a free tier with certain usage limitations (e.g., rate limits or capacity constraints).
• ChatGPT Plus: Offers an upgraded experience (priority access, faster responses, GPT-4 usage) at a fixed monthly subscription cost.
• Potential enterprise offerings: OpenAI has introduced ChatGPT for enterprise with additional features, but that is a different arrangement than typical usage.

Chatbot via OpenAI API

• Pay per usage (tokens): You pay for the volume of tokens processed (input + output). Costs vary depending on the model used (GPT-3.5, GPT-4, etc.) and the prompt size.
• More predictable or flexible scaling: If you build a large-scale application, you can estimate and manage costs at scale. For small usage, you only pay for what you use.
• Fine-tuning and other advanced features: Fine-tuning and embedding usage may incur additional costs.

Reason: ChatGPT’s subscription is a packaged service with usage constraints baked in, whereas the API’s billing is a consumption-based model, ideal for custom applications that may have varying or large-scale usage.

5. Integration with Existing Systems

ChatGPT

• Standalone: ChatGPT primarily lives as a single, user-facing interface (i.e., the ChatGPT website).
• Limited direct integrations: You can manually copy answers into other systems, but ChatGPT doesn’t (by default) integrate with external apps. There are third-party browser plugins and some community-led “integrations,” but official options are limited (though ChatGPT Plugins offer some expansions within certain constraints).

Chatbot via OpenAI API

• Deep integrations: You can build your chatbot into CRM systems, help desks, websites, mobile apps, Slack, or anywhere else via standard HTTP requests.
• Customized workflows: You can connect to internal databases, knowledge bases, or external APIs. You can orchestrate multiple calls, building advanced workflows (e.g., chain-of-thought reasoning combined with knowledge base lookups).

Reason: The API is designed for custom development, allowing you to integrate the language model’s capabilities into any environment or workflow you control.

6. Model Versioning and Updates

ChatGPT

• Automatic updates: OpenAI periodically updates ChatGPT’s model or interface. You do not control the timing or specifics of these updates.
• Fixed environment: End-users see minimal version information (e.g., GPT-3.5 vs. GPT-4), and you cannot revert to older ChatGPT versions once updates are released.

Chatbot via OpenAI API

• Choice of model: You decide which model (e.g., GPT-3.5, GPT-4) to use, and you can specify the model version in the API call to maintain consistency.
• Gradual upgrades: You can test new models in a sandbox, verify performance, and then switch production to newer versions at your own pace. This avoids unexpected changes in behavior due to model updates.

Reason: ChatGPT is a managed service that OpenAI updates automatically, whereas the API user has the flexibility to pick and lock specific model versions, ensuring stability and controlled rollouts.

7. Support and Troubleshooting

ChatGPT

• Limited direct support: For the free tier, support channels are mainly community forums and self-help resources. ChatGPT Plus subscribers get priority support but it’s still relatively limited compared to enterprise-level APIs.
• No debugging at the code level: Since you do not control the backend, you cannot “debug” ChatGPT’s environment. You can only report issues or rely on official announcements from OpenAI.

Chatbot via OpenAI API

• Developer-focused: You have access to API documentation, sample code, and can debug issues in your codebase. OpenAI also provides developer support channels.
• In-house logs and telemetry: Because you host the solution, you can implement logging and monitoring at multiple layers (frontend, middleware, API usage) to troubleshoot issues.

Reason: The API is aimed at developers who require technical control and insights, while ChatGPT is a simpler end-user interface with limited need (and opportunity) for deep debugging.

8. Use Cases and Target Users

ChatGPT

• End-users or small businesses: Ideal for quick answers, creative writing, brainstorming, or general productivity without needing custom integration.
• Prototyping or experimenting: People who want to quickly test GPT’s capabilities without building a full application or writing code.

Chatbot via OpenAI API

• Enterprise or large-scale projects: Companies needing internal tools, automated customer support, analytics, or integrated solutions within existing software.
• Specialized domains: Developers building domain-specific assistants (legal, healthcare, finance, etc.) with controlled vocabulary, compliance needs, or custom data.

Reason: ChatGPT is an “off-the-shelf” tool good for general tasks, while the API is meant for building specialized or large-scale conversational interfaces integrated into various products and workflows.

Overall, ChatGPT is best for individuals and organizations that want a straightforward, user-friendly chatbot without managing any infrastructure, while a custom chatbot via the OpenAI API is for those needing deeper customization, integration with existing workflows, and full control over data and deployment.